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The New Multi-Mission Altimeter Data Set Reprocessed Over 20 Years

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The New Multi-Mission Altimeter Data Set Reprocessed Over 20 Years Ocean Sci., 12, 1067–1090, 2016 www.ocean-sci.net/12/1067/2016/ doi:10.5194/os-12-1067-2016 © Author(s) 2016. CC Attribution 3.0 License. DUACS DT2014: the new multi-mission altimeter data set reprocessed over 20 years Marie-Isabelle Pujol1,*, Yannice Faugère1,*, Guillaume Taburet1, Stéphanie Dupuy1, Camille Pelloquin1, Michael Ablain1, and Nicolas Picot2 1Collecte Localisation Satellites, Parc Technologique du Canal, 8–10 rue Hermès, 31520 Ramonville-Saint-Agne, France 2Centre National Etudes Spatiales, 18 Avenue Edouard Belin, 31400 Toulouse, France *These authors contributed equally to this work. Correspondence to: Marie-Isabelle Pujol ([email protected]) Received: 16 December 2015 – Published in Ocean Sci. Discuss.: 18 January 2016 Revised: 26 July 2016 – Accepted: 17 August 2016 – Published: 9 September 2016 Abstract. The new DUACS DT2014 reprocessed products the mesoscale reaches nearly 10 % of the error observed with have been available since April 2014. Numerous innovative DT2010. DT2014 also presents an improved coastal signal changes have been introduced at each step of an extensively with a nearly 2 to 4 % mean error reduction. High-latitude revised data processing protocol. The use of a new 20-year areas are also more accurately represented in DT2014, with altimeter reference period in place of the previous 7-year an improved consistency between spatial coverage and sea reference significantly changes the sea level anomaly (SLA) ice edge position. An error budget is used to highlight the patterns and thus has a strong user impact. The use of up- limitations of the new gridded products, with notable errors to-date altimeter standards and geophysical corrections, re- in areas with strong internal tides. duced smoothing of the along-track data, and refined map- ping parameters, including spatial and temporal correlation- scale refinement and measurement errors, all contribute to an improved high-quality DT2014 SLA data set. Although 1 Introduction all of the DUACS products have been upgraded, this paper focuses on the enhancements to the gridded SLA products Since its inception in late 1997, the DUACS (Data Unifica- over the global ocean. As part of this exercise, 21 years of tion and Altimeter Combination System) has produced and data have been homogenized, allowing us to retrieve accurate delivered high-quality along-track (L3) and multi-mission large-scale climate signals such as global and regional MSL gridded (L4) altimeter products that are used by a large vari- trends, interannual signals, and better refined mesoscale fea- ety of users for different applications. The data are available tures. both in near real time (NRT), with a delay of a few hours to 1 An extensive assessment exercise has been carried out on day, and in a delayed time (DT) mode with a delay of a few this data set, which allows us to establish a consolidated er- months. A complete reprocessing of the DT products is done ror budget. The errors at mesoscale are about 1.4 cm2 in low- every 4 years approximately. Over the last 2 decades, suc- variability areas, increase to an average of 8.9 cm2 in coastal cessive papers have described the evolution of the DUACS regions, and reach nearly 32.5 cm2 in high mesoscale activ- system and its associated products (Le Traon and Hernandez, ity areas. The DT2014 products, compared to the previous 1992; Le Traon and Ogor, 1998; Le Traon and Dibarboure, DT2010 version, retain signals for wavelengths lower than 1999; Le Traon et al., 1995, 2003; Ducet et al., 2000; Pujol ∼ 250 km, inducing SLA variance and mean EKE increases and Lamicol, 2005; Dibarboure et al., 2011). The quality of of, respectively, C5.1 and C15 %. Comparisons with in- DUACS products is affected by several factors, such as the dependent measurements highlight the improved mesoscale altimeter constellation used for input (Pascual et al., 2006; representation within this new data set. The error reduction at Dibarboure et al., 2011), the choices of altimeter standards (Dibarboure et al., 2011; Ablain et al., 2015), and improve- Published by Copernicus Publications on behalf of the European Geosciences Union. 1068 M.-I. Pujol et al.: The new multi-mission altimeter data set ments in data processing algorithms (Ducet et al., 2000; Dus- are computed directly at the 1=4◦ × 1=4◦ Cartesian grid res- surget et al., 2011; Griffin and Cahill, 2012; Escudier et al., olution. Other changes that have been implemented allow us 2013). to correct a number of different anomalies that were detected This paper addresses a new global reprocessing that covers in the previous DT2010 product suite. The resulting quality the entire altimeter period and allows us, for the first time, to of the sea surface height estimate is improved. In this paper generate a gridded time series of more than 20 years, iden- we introduce DT2014, the latest version of the Aviso SLA tified here as DT2014. The period starts at the beginning of product, and evaluate its improvements with respect to the the altimeter era and ranges from 1993 to 2013. Measure- previous version. ments from 10 altimeter missions (repeat track and geodetic The paper is organized as follows: details of the L3/L4 orbits) have been used: the TOPEX/Poseidon (TP) and Jason altimeter data processing used for the generation of the series (Jason-1 (J1) and OSTM/Jason-2 (J2)), ERS-1, ERS- DT2014 products are presented in Sect. 2. In Sect. 3, re- 2 and ENVISAT (EN), Geosat Follow On (GFO), Cryosat-2 sults obtained from the DT2014 SLA reprocessed products (C2), Saral/AltiKa (AL) and Haiyang-2A (HY-2A). DT2014 are compared with equivalent DT2010 results, focusing on represents a major upgrade of the previous version, DT2010 the mesoscales and coastal areas. In the same section, for the (Dibarboure et al., 2011), but pursues the same objectives first time, we make an estimate of the L4 SLA product er- that comprise the generation of time series that are homo- rors. Finally, a summary of the key results obtained is given geneous in terms of altimeter standards and processing with in Sect. 4. an optimal content at both mesoscales and large scales. To achieve this objective, various algorithms and corrections developed by the research community and through differ- 2 Data processing ent projects and programs such as the French SALP/Aviso, the European Myocean2, and the European Space Agency 2.1 Altimeter standards (ESA) Climate Change Initiative projects are used. The de- velopment of regional experimental DUACS products in the The altimeter standards used for DT2014 were selected tak- framework of scientific oceanographic campaigns such as ing advantage of the work performed during the first phase KEOPS-2 (d’Ovidio et al., 2015) was also valuable for lo- of the Sea Level Climate Change Initiative (SL_cci) led by cal assessments of the improvements, prior to the imple- the European Space Agency in 2011–2013. The objective of mentation and release of the global product. However, one this project was to generate optimal reprocessed products for of the main priorities was to improve the monitoring of the climate applications, notably global and regional mean sea mesoscales in the global ocean. Indeed, recent papers (Dus- level trends. As part of this exercise, a rigorous selection pro- surget et al., 2011; Chelton et al., 2011; Escudier at al., 2013) cess was put in place. This process, as well as all the selected have shown that despite the accuracy of the DT2010 gridded standards, is described by ESA SL_cci (2015) and Ablain et products, the interpolation of mesoscale signals is limited al. (2015). As recommended by the SL_cci project, several by the anisotropy of the altimetry observing system. Finally, major standards were implemented in the DT2014 products finer-scale signals contained in the altimeter raw measure- compared to DT2010. The details of the altimeter standards ments are not really exploited and provided in the higher- used in the DT2014 products are given in Table 1. level DUACS products (L3 and L4). In addition to these One of the most dramatic improvements comes from the mesoscale retrieval improvements and to satisfy the needs use of ERA-Interim reanalysis (from the European Centre of different Aviso users, the new DT2014 reprocessing prod- for Medium-Range Weather Forecasts; ECMWF; Dee et al., uct also benefits from climate standards and corrections that 2011) instead of operational ECMWF fields for the calcu- do not degrade the mesoscale signals. Thus, the different lation of the dry-tropospheric and other dynamical atmo- choices and trade-offs that have been made in the genera- spheric corrections. Important improvements have been ob- tion of the DT2014 reprocessing are described in detail in served over the first altimetry decade (1993–2003) at the this paper. mesoscale and, especially, at high latitudes, allowing a bet- The DT2014 reprocessing is characterized by important ter estimation of long-term regional mean sea level trends changes in terms of altimeter standards, data processing and (Carrere et al., 2016). However, the evaluations also showed formats. The main changes consist of referencing the SLA that the use of this correction slightly degraded the variance products to a new altimeter reference period, taking advan- of the signal in shallow water areas for the second altimetry tage of the 20 years of measurements that are currently decade. To ensure an optimal description of these signals for available and optimizing along-track random noise reduc- Aviso/Myocean-2 users, the operational ECMWF fields were tion, which affected a large part of the physical signal in the used from 2001 onwards. DT2010 version. These changes make a significant impact Another major improvement has been achieved by us- on the physical content of the SLA and derived products. ing new orbit solutions for different altimeter missions: The gridded SLA products are constructed using more ac- REAPER-combined orbit solutions (Rudenko et al., 2012) curate parameters (e.g., correlation scales, error budgets) and for ERS-1 and ERS-2, CNES GDR-D orbit solutions Ocean Sci., 12, 1067–1090, 2016 www.ocean-sci.net/12/1067/2016/ 1090 www.ocean-sci.net/12/1067/2016/ Ocean Sci., 12, 1067– M.-I.
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